DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant’s additional arguments, filed January 27, 2026, have been noted; however, these arguments are moot in view of the rejection below.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-2, 8-10, 13 and 21-24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mammou et al. (US 2021/0312670 A1, already of record, referred to herein as “Mammou”) in view of Van der Auwera et a. (US 2023/0105931 A1, referred to herein as “Van der Auwera”).
Regarding claim 1, Mammou discloses: A method of encoding a point cloud into a bitstream of
encoded point cloud data (Mammou: Fig. 2A, paragraph [0058], disclosing point cloud encoding
methods), each point of the point cloud being associated with a radius responsive to a distance of the point from a
sensor that captured the point (Mammou: paragraph [0178], disclosing use of a sensor to capture a 3D image for point cloud coding; paragraph [0077], disclosing point cloud prediction using polar
coordinates), the method comprising:
obtaining a predicted radius representative of a prediction of a radius of a point of the point cloud from
prediction data (PD) (Mammou: Fig. 2A, paragraphs [0070] – [0072], disclosing prediction of point
cloud nodes; paragraph [0077], disclosing use of polar prediction including a predicted radius);
obtaining a… residual of a point of the point cloud between the radius of said point and the predicted
radius (Mammou: paragraph [0083], disclosing that residuals of the predicted point cloud nodes may
be determined; paragraph [0077], disclosing use of polar coordinates to represent current and
predicted nodes);
selecting a context based on the prediction data (Mammou: Fig. 13A, paragraph [0188], disclosing
selection of a context for predictive coding); and
context-based entropy encoding the magnitude of the… residual based the selected context (Mammou:
Fig. 13A, paragraphs [0083] and [0188], disclosing context-based entropy encoding of residual data).
Mammou does not explicitly disclose obtaining a radius residual and context-based encoding the radius residual.
However, Van der Auwera discloses obtaining a radius residual and context-based encoding the radius residual (Van der Auwera: paragraph [0160], disclosing computation of a radius residual between a current point’s radius and a predicted radius; paragraph [0161], disclosing that the radius residual may be context coded with an arithmetic coder).
At the time the application was filed, it would have been obvious for a person having ordinary skill in the art to use the radius residual of Van der Auwera in the method of Mammou.
One would have been motivated to modify Mammou in this manner in order to improve prediction accuracy and thus coding efficiency (Van der Auwera: paragraph [0025]). Additionally, Mammou and Van der Auwera are directed to the same field of endeavor—namely, point cloud encoding of data using polar coordinates (Mammou: paragraphs [0002] and [0077]; Van der Auwera: paragraphs [0003] and [0128]).
Regarding claim 2, Mammou and Van der Auwera disclose: A method of decoding a point cloud from a bitstream of encoded point cloud data (Mammou: Fig. 2A, paragraph [0058], disclosing point cloud encoding and decoding methods), each point of the point cloud being associated with a radius responsive to a distance of the point from a sensor that captured the point (Mammou: paragraph [0178], disclosing use of a sensor to capture a 3D image for point cloud coding; paragraph [0077], disclosing point cloud prediction using polar coordinates), the method comprising:
obtaining a predicted radius representative of a prediction of a radius of a point of the point cloud from
prediction data (PD) (Mammou: Fig. 2A, paragraphs [0070] – [0072], disclosing prediction of point
cloud nodes; paragraph [0077], disclosing use of polar prediction including a predicted radius); selecting a context based on the prediction data (PD) (Mammou: Fig. 13A, paragraph [0188],
disclosing selection of a context for predictive coding); and
context-based entropy decoding the magnitude of the radius residual based the selected context (Mammou:
Figs. 13A-B, paragraphs [0083], [0188] and [0193], disclosing context-based entropy encoding of
residual data; Van der Auwera: paragraph [0160], disclosing computation of a radius residual between a current point’s radius and a predicted radius; paragraph [0161], disclosing that the radius residual may be context coded with an arithmetic coder).
The motivation for combining Mammou and Van der Auwera has been discussed in connection with claim 1, above.
Regarding claim 8, Mammou and Van der Auwera disclose: The method of claim 1, wherein each point of the point cloud being further associated with an azimuthal angle responsive to a capture angle of the sensor, a predicted azimuthal angle being obtained by adding an azimuthal angle obtained from the prediction data (PD) with an azimuthal angle shift defined as a product of an integer number (m) by an elementary azimuthal step, and wherein the prediction data comprises said integer number (m) (Mammou: paragraph [0103], disclosing acquisition of data based on an azimuth angle; paragraphs [0077] and [0106] – [0108], disclosing a predicted azimuth angle based on an azimuth angle shift).
Regarding claim 9, Mammou and Van der Auwera disclose: The method of claim 1, wherein the prediction data (PD) is encoded into the bitstream (Mammou: paragraphs [0082] and [0092, disclosing encoding of prediction data into the bitstream).
Regarding claim 10, Mammou discloses: The method of claim 1, wherein a series of bits,
representative of the magnitude of the radius residual, is encoded as a unary code and said unary code is context-based
entropy encoded based on the selected context, or a series of bits, representative of the magnitude of the radius residual,
is encoded as an Exponential-Golomb code and said Exponential-Golomb code is context-based entropy encoded
based on the selected context (Mammou: paragraph [0188], disclosing context-based entropy encoding
using Exponential-Golomb code; Van der Auwera: paragraph [0160], disclosing computation of a radius residual between a current point’s radius and a predicted radius; paragraph [0161], disclosing that the radius residual may be context coded with an arithmetic coder).
The motivation for combining Mammou and Van der Auwera has been discussed in connection with claim 1, above.
Regarding claim 13, Mammou discloses: An apparatus comprising one or more processors
(Mammou: paragraphs [0054] and [0199] – [0200], disclosing implementation via processors)
configured to carry out a method of encoding a point cloud into a bitstream of encoded point cloud data (Mammou:
Fig. 2A, paragraph [0058], disclosing point cloud encoding methods), each point of the point cloud being
associated with a radius responsive to a distance of the point from a sensor that captured the point (Mammou:
paragraph [0178], disclosing use of a sensor to capture a 3D image for point cloud coding; paragraph
[0077], disclosing point cloud prediction using polar coordinates), the method comprising:
obtaining a predicted radius representative of a prediction of a radius of a point of the point cloud from
prediction data (PD) (Mammou: Fig. 2A, paragraphs [0070] – [0072], disclosing prediction of point
cloud nodes; paragraph [0077], disclosing use of polar prediction including a predicted radius);
obtaining a radius residual of a point of the point cloud between the radius of said point and the predicted
radius (Mammou: paragraph [0083], disclosing that residuals of the predicted point cloud nodes may
be determined; paragraph [0077], disclosing use of polar coordinates to represent current and
predicted nodes; Van der Auwera: paragraph [0160], disclosing computation of a radius residual between a current point’s radius and a predicted radius; paragraph [0161], disclosing that the radius residual may be context coded with an arithmetic coder);
selecting a context based on the prediction data (PD) (Mammou: Fig. 13A, paragraph [0188],
disclosing selection of a context for predictive coding); and
context-based entropy encoding the magnitude of the residual radius based the selected context (Mammou:
Fig. 13A, paragraphs [0083] and [0188], disclosing context-based entropy encoding of residual data).
The motivation for combining Mammou and Van der Auwera has been discussed in connection with claim 1, above.
Regarding claim 21, Mammou and Van der Auwera disclose: The method of claim 2, wherein each point of the point cloud being further associated with an azimuthal angle responsive to a capture angle of the sensor, a predicted azimuthal angle being obtained by adding an azimuthal angle obtained from the prediction data (PD) with an azimuthal angle shift defined as a product of an integer number (m) by an elementary azimuthal step and wherein the prediction data comprises said integer number (m) (Mammou: paragraph [0103], disclosing acquisition of data based on an azimuth angle; paragraphs [0077] and [0106] – [0108], disclosing a predicted azimuth angle based on an azimuth angle shift).
Regarding claim 22, Mammou and Van der Auwera disclose: The method of claim 2, wherein the prediction data (PD) is decoded from the bitstream (Mammou: paragraphs [0082] and [0092, disclosing encoding of prediction data into the bitstream; paragraph [0060], disclosing decoding of encoded data).
Regarding claim 23, Mammou and Van der Auwera disclose: The method of claim 2, wherein a series of bits, representative of the magnitude of the residual radius, is decoded as a unary code and said unary code is context-based entropy decoded based on the selected context; or a series of bits, representative of the magnitude of the radius residual, is decoded as an Exponential-Golomb code and said Exponential-Golomb code is context-based entropy decoded based on the selected context (Mammou: paragraph [0188], disclosing context-based entropy encoding using Exponential-Golomb code; Van der Auwera: paragraph [0160], disclosing computation of a radius residual between a current point’s radius and a predicted radius; paragraph [0161], disclosing that the radius residual may be context coded with an arithmetic coder).
The motivation for combining Mammou and Van der Auwera has been discussed in connection with claim 1, above.
Regarding claim 24, Mammou and Van der Auwera disclose: An apparatus comprising one or more processors configured to carry out the method claimed in claim 2 (Mammou: paragraphs [0054] and [0199] – [0200], disclosing implementation via processors).
Claim(s) 3-7 and 16-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mammou in view of Van der Auwera as applied to claim 1/2 above, and further in view of Ramasubramonian et al. (US 2022/0207780 A1, already of record, referred to herein as “Ramasubramonian”).
Regarding claim 3, Mammou and Van der Auwera disclose: The method of claim 1, as discussed above.
Mammou and Van der Auwera do not explicitly disclose: wherein the method further comprises context-based entropy encoding based on the selected context, into the bitstream, a binary data (fo) indicating whether the magnitude of the radius residual equals 0 or not.
However, Ramasubramonian discloses: wherein the method further comprises context-based entropy
encoding based on the selected context, into the bitstream, a binary data (fo) indicating whether the magnitude of the radius residual equals 0 or not (Ramasubramonian: paragraph [0203], disclosing an “equal_to_zero” flag
for indicating that the magnitude of a residual radius is zero).
At the time the application was effectively filed, it would have been obvious for a person
having ordinary skill in the art to use the residual information of Ramasubramonian in the method
of Mammou and Van der Auwera.
One would have been motivated to modify Mammou and Van der Auwera in this manner in order to signal information that may improve coding efficiency such as when a radius does not change much across points of the point cloud (Ramasubramonian: paragraphs [0015] and [0203]). Additionally, Mammou, Van der Auwera, and Ramasubramonian are directed to the same field of endeavor—namely, point cloud encoding of data using polar coordinates (Mammou: paragraphs [0002] and [0077]; Van der Auwera: paragraphs [0003] and [0128]; Ramasubramonian: paragraph [0015]).
Regarding claim 4, Mammou, Van der Auwera and Ramasubramonian disclose: The method of claim 3, wherein the magnitude of the radius residual rres minus 1 is context-based entropy encoded based on the selected context (Mammou: paragraph [0086], disclosing node selection based on magnitude of prediction residual; Van der Auwera: paragraph [0160], disclosing computation of a radius residual between a current point’s radius and a predicted radius; paragraph [0161], disclosing that the radius residual may be context coded with an arithmetic coder; Ramasubramonian: paragraph [0204], Table 1, disclosing binary data for residual radius magnitude in context-based encoding; paragraph [0207], disclosing signaling of binary data minus 1 values).
The motivation for combining Mammou, Van der Auwera, and Ramasubramonian has been discussed in connection with claim 3, above.
Regarding claim 5, Mammou, Van der Auwera, and Ramasubramonian disclose: The method of claim 1, wherein the method further comprises context-based entropy encoding, into the bitstream, a binary data (fi) indicating whether the magnitude of the radius residual is equal to or greater than 1 (Mammou: paragraph [0086], disclosing node selection based on magnitude of prediction residual; Van der Auwera: paragraph [0160], disclosing computation of a radius residual between a current point’s radius and a predicted radius; paragraph [0161], disclosing that the radius residual may be context coded with an arithmetic coder; Ramasubramonian: paragraph [0204], Table 1, disclosing binary data for residual radius magnitude in context-based encoding including values equal to or greater than 1).
The motivation for combining Mammou, Van der Auwera, and Ramasubramonian has been discussed in connection with claim 3, above.
Regarding claim 6, Mammou, Van der Auwera, and Ramasubramonian disclose: The method of claim 5, wherein the magnitude of the radius residual rres minus 2 is context-based entropy encoded based on the selected context (Mammou: paragraph [0086], disclosing node selection based on magnitude of prediction residual; Van der Auwera: paragraph [0160], disclosing computation of a radius residual between a current point’s radius and a predicted radius; paragraph [0161], disclosing that the radius residual may be context coded with an arithmetic coder; Ramasubramonian: paragraph [0204], Table 1, disclosing binary data for residual radius magnitude in context-based encoding; paragraph [0207], disclosing signaling of binary data minus 2 values).
The motivation for combining Mammou, Van der Auwera, and Ramasubramonian has been discussed in connection with claim 3, above.
Regarding claim 7, Mammou, Van der Auwera, and Ramasubramonian disclose: The method of claim 1, wherein the predicted radius is obtained from a predictor selected from a list of at least one predictor comprising each a predicted radius, and wherein prediction data comprises a predictor index that points to the predictor of the list of said at least one predictor (Ramasubramonian: paragraph [0203], disclosing use of a residual radius; paragraph [0244] and [0261], disclosing that an index may be signaled that specifies a point chosen for prediction).
The motivation for combining Mammou, Van der Auwera, and Ramasubramonian has been discussed in connection with claim 3, above.
Regarding claim 16, Mammou, Van der Auwera, and Ramasubramonian disclose: The method of claim 2, wherein the method further comprises context-based entropy decoding based on the selected context, from the bitstream, a binary data (fo) indicating whether the magnitude of the radius residual equals 0 or not (Ramasubramonian: paragraph [0203], disclosing an “equal_to_zero” flag for indicating that the magnitude of a residual radius is zero; Van der Auwera: paragraph [0160], disclosing computation of a radius residual between a current point’s radius and a predicted radius; paragraph [0161], disclosing that the radius residual may be context coded with an arithmetic coder).
The motivation for combining Mammou, Van der Auwera, and Ramasubramonian has been discussed in connection with claim 3, above.
Regarding claim 17, Mammou, Van der Auwera, and Ramasubramonian discloses: The method of claim 16, wherein the magnitude of the radius residual rres minus 1 is context-based entropy decoded based on the selected context (Mammou: paragraph [0086], disclosing node selection based on magnitude of prediction residual; Van der Auwera: paragraph [0160], disclosing computation of a radius residual between a current point’s radius and a predicted radius; paragraph [0161], disclosing that the radius residual may be context coded with an arithmetic coder; Ramasubramonian: paragraph [0204], Table 1, disclosing binary data for residual radius magnitude in context-based encoding; paragraph [0207], disclosing signaling of binary data minus 1 values).
The motivation for combining Mammou, Van der Auwera, and Ramasubramonian has been discussed in connection with claim 3, above.
Regarding claim 18, Mammou, Van der Auwera, and Ramasubramonian disclose: The method of claim 2, wherein the method further comprises context-based entropy decoding from the bitstream, a binary data (fi) indicating whether the magnitude of the radius residual is equal to or greater than 1 (Mammou: paragraph [0086], disclosing node selection based on magnitude of prediction residual; Van der Auwera: paragraph [0160], disclosing computation of a radius residual between a current point’s radius and a predicted radius; paragraph [0161], disclosing that the radius residual may be context coded with an arithmetic coder; Ramasubramonian: paragraph [0204], Table 1, disclosing binary data for residual radius magnitude in context-based encoding including values equal to or greater than 1).
The motivation for combining Mammou, Van der Auwera, and Ramasubramonian has been discussed in connection with claim 3, above.
Regarding claim 19, Mammou, Van der Auwera, and Ramasubramonian disclose: The method of claim 18, wherein the magnitude of the radius residual rres minus 2 is context-based entropy decoded based on the selected context (Mammou: paragraph [0086], disclosing node selection based on magnitude of prediction residual; Van der Auwera: paragraph [0160], disclosing computation of a radius residual between a current point’s radius and a predicted radius; paragraph [0161], disclosing that the radius residual may be context coded with an arithmetic coder; Ramasubramonian: paragraph [0204], Table 1, disclosing binary data for residual radius magnitude in context-based encoding; paragraph [0207], disclosing signaling of binary data minus 2 values).
The motivation for combining Mammou, Van der Awera, and Ramasubramonian has been discussed in connection with claim 3, above.
Regarding claim 20, Mammou, Van der Auwera, and Ramasubramonian disclose: The method of claim 2, wherein the predicted radius is obtained from a predictor selected from a list of at least one predictor comprising each a predicted radius, and wherein prediction data comprises a predictor index that points to the predictor of the list of said at least one predictor (Ramasubramonian: paragraph [0203], disclosing use of a residual radius; paragraph [0244] and [0261], disclosing that an index may be signaled that specifies a point chosen for prediction).
The motivation for combining Mammou, Van der Auwera, and Ramasubramonian has been discussed in connection with claim 3, above.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Christopher Braniff whose telephone number is (571)270-5009. The examiner can normally be reached M-F 7AM to 4PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Thai Tran can be reached at (571) 272-7382. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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CHRISTOPHER T. BRANIFF
Primary Examiner
Art Unit 2484
/CHRISTOPHER BRANIFF/Primary Examiner, Art Unit 2484
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